DEF CON · 2018DC26
Adversarial Patches
Sven Cattell
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DEF CON · 2018DC26
AI DevOps Behind the Scenes of a Global AV Company
Alex Long
DEF CON · 2018DC26
Automated Planning for the Automated Red Team
Andy Applebaum
DEF CON · 2018DC26
Beyond Adversarial Learning Security Risks in AI Implementations
Kang Li
DEF CON · 2018DC26
Chatting with Your Programs to Find Vulnerabilities
Chris Gardner
DEF CON · 2018DC26
DeepPhish Simulating the Malicious Use of AI
Ivan Torroledo
DEF CON · 2018DC26
Detecting Web Attacks with Recurrent Neural Networks
Fedor Sakharov
DEF CON · 2018DC26
Generating Labeled Data From Adversary Sims with MITRE ATT&CK
Brian Genz
DEF CON · 2018DC26
Hunting the Ethereum Smart Contract Color Inspired Inspection
TonTon Huang
DEF CON · 2018DC26
Identifying and Correlating Anomalies in Internetwide Scan
Andrew Morris
DEF CON · 2018DC26
It is a Beautiful Day in the Malware Neighborhood
Matt
DEF CON · 2018DC26
JMPgate Accelerating Reverse Engineering Into Hyperspace
Rob Brandon
DEF CON · 2018DC26
Malware Panel
drhyrum
DEF CON · 2018DC26
Rapid Anomaly Detection via Ransom Note File Classification
Mark Mager
DEF CON · 2018DC26
StuxNNet Practical Live Memory Attacks on Machine Learning
Raphael Norwitz
DEF CON · 2018DC26
The Current State of Adversarial Machine Learning
infosecanon
DEF CON · 2018DC26
Towards a Framework to Quantitatively Assess AI Safety
Shankar and Kumar
DEF CON · 2018DC26
WhiteRabbit Combining Threat Intelligence Public Blockchain
trustartech
DEF CON · 2018DC26
Learning to Listen Machine Learning for Adaptive Wireless
Dunlap